One Problem, Many Solutions: Simple Statistical Approaches Help Unravel the Complexity of the Immune System in an Ecological Context

The immune system is a complex collection of interrelated and overlapping solutions to the problem of disease. To deal with this complexity, researchers have devised multiple ways to measure immune function and to analyze the resulting data. In this way both organisms and researchers employ many tactics to solve a complex problem. One challenge facing ecological immunologists is the question of how these many dimensions of immune function can be synthesized to facilitate meaningful interpretations and conclusions. We tackle this challenge by employing and comparing several statistical methods, which we used to test assumptions about how multiple aspects of immune function are related at different organizational levels. We analyzed three distinct datasets that characterized 1) species, 2) subspecies, and 3) among- and within-individual level differences in the relationships among multiple immune indices. Specifically, we used common principal components analysis (CPCA) and two simpler approaches, pair-wise correlations and correlation circles. We also provide a simple example of how these techniques could be used to analyze data from multiple studies. Our findings lead to several general conclusions. First, relationships among indices of immune function may be consistent among some organizational groups (e.g. months over the annual cycle) but not others (e.g. species); therefore any assumption of consistency requires testing before further analyses. Second, simple statistical techniques used in conjunction with more complex multivariate methods give a clearer and more robust picture of immune function than using complex statistics alone. Moreover, these simpler approaches have potential for analyzing comparable data from multiple studies, especially as the field of ecological immunology moves towards greater methodological standardization

Genome Sequence of Yersinia pestis KIM

We present the complete genome sequence of Yersinia pestis KIM, the etiologic agent of bubonic and pneumonic plague. The strain KIM, biovar Mediaevalis, is associated with the second pandemic, including the Black Death. The 4.6-Mb genome encodes 4,198 open reading frames (ORFs). The origin, terminus, and most genes encoding DNA replication proteins are similar to those of Escherichia coli K-12. The KIM genome sequence was compared with that of Y. pestis CO92, biovar Orientalis, revealing homologous sequences but a remarkable amount of genome rearrangement for strains so closely related. The differences appear to result from multiple inversions of genome segments at insertion sequences, in a manner consistent with present knowledge of replication and recombination. There are few differences attributable to horizontal transfer. The KIM and E. coli K-12 genome proteins were also compared, exposing surprising amounts of locally colinear “backbone,” or synteny, that is not discernible at the nucleotide level. Nearly 54% of KIM ORFs are significantly similar to K-12 proteins, with conserved housekeeping functions. However, a number of E. coli pathways and transport systems and at least one global regulator were not found, reflecting differences in lifestyle between them. In KIM-specific islands, new genes encode candidate pathogenicity proteins, including iron transport systems, putative adhesins, toxins, and fimbriae